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How much do night shift data annotation tech jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for night shift data annotation tech in the United States is $22.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What is a night shift data annotation tech?

Night Shift Data Annotation Techs are professionals who work overnight hours to label, tag, or categorize data—such as images, audio, or text—for use in machine learning and artificial intelligence systems. Their work ensures that data sets are accurate and well-organized so that algorithms can be trained effectively. These technicians often use specialized software tools and must pay close attention to detail. Working the night shift may involve supporting 24/7 operations, meeting tight deadlines, or collaborating remotely with global teams.

What skills and qualifications are needed to thrive as a night shift data annotation tech?

To thrive as a Night Shift Data Annotation Tech, you need strong attention to detail, basic computer literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Experience with annotation platforms, spreadsheet tools, and sometimes workflow management systems is typically required. Reliability, self-motivation, and effective time management are crucial soft skills for working independently during overnight hours. These skills and qualities ensure consistent, accurate data labeling that supports machine learning projects and meets tight deadlines.

What are common challenges faced by night shift data annotation techs and how can they be managed?

Night Shift Data Annotation Techs often encounter challenges such as maintaining focus during late hours and managing fatigue. Working overnight can require extra attention to detail to avoid errors, especially when handling large volumes of data. Many professionals address these challenges by establishing consistent sleep schedules, taking short breaks to stay alert, and using productivity tools to track progress. Additionally, strong communication with team members and supervisors during shift overlaps ensures smooth handoffs and clarifies any ambiguities in annotation guidelines.

What is the difference between Night Shift Data Annotation Tech vs Night Shift Data Labeler?

AspectNight Shift Data Annotation TechNight Shift Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentData annotation platforms, remote or on-siteData labeling tasks, often remote or on-site
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, autonomous vehicles
Job FocusAnnotating data for training AI modelsLabeling data to improve AI accuracy

Both roles involve working with data to support AI development, often in similar environments. The main difference is that Data Annotation Tech may focus more on using specialized tools and platforms, while Data Labelers may perform more straightforward labeling tasks. Both positions require attention to detail and are essential in AI training processes.

What are popular job titles related to Night Shift Data Annotation Tech jobs?

For Night Shift Data Annotation Tech jobs, the most frequently searched job titles are:

Night Shift Data Annotation Tech jobs near you
Infographic showing various Night Shift Data Annotation Tech job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $47,512 per year, or $22.8 per hour.

AI Training Specialist (Data Annotation)

Tampa, FL • Remote

Remote Talent Cloud
See more jobs at Remote Talent Cloudexternal

$20/hr

Contractor

Re-posted 14 days ago

Job description

As an AI Training Specialist (Data Annotation), you'll play a key role in helping train and improve artificial intelligence (AI) systems. Your work will directly support how AI models learn to recognize text, images, and other data accurately.

Your main responsibilities will include:

  • Labeling and categorizing data (such as text, images, or short videos) according to detailed project guidelines
  • Reviewing and verifying data for accuracy, consistency, and completeness
  • Identifying and flagging any errors, inconsistencies, or unclear data
  • Following clear annotation instructions to ensure high-quality results
  • Meeting productivity and accuracy goals within project timelines
  • Maintaining confidentiality and adhering to all data security standards

Requirements

We're looking for detail-oriented individuals who are comfortable working independently and enjoy structured, accuracy-focused tasks. The ideal candidate will have:

  • This is a fully remote position, but you must be located within the United States
  • Excellent attention to detail and strong organizational skills
  • A reliable Internet connection and computer
  • The ability to focus for extended periods and follow detailed written instructions
  • Strong written communication skills in English
  • Previous data annotation, labeling, or transcription experience is a plus, but not required

Benefits

  • Fully remote: work from anywhere within the United States
  • Full-time and part-time available
  • Competitive hourly pay from $20/hr
  • Training provided for all annotation tools and workflows
  • Gain hands-on experience supporting real-world AI training projects
  • Be part of a growing remote team working on cutting-edge technology

Apply